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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Volatile Analysis by Pyrolysis of Regolith (Vapor) on the Moon using Mass Spectrometry

The identification of lunar resources such as water is a fundamental component of the the NASA Vision for Space Exploration. The Lunar Prospector mission detected high concentrations of hydrogen at the lunar poles that may indicate the presence of water or other volatiles in the lunar regolith [1]. One explanation for the presence of enhanced hydrogen in permanently shadowed crater regions is long term trapping of water-ice delivered by comets, asteroids, and other meteoritic material that have bombarded the Moon over the last 4 billion years [2]. It is also possible that the hydrogen signal at the lunar poles is due to hydrogen implanted by the solar wind which is delayed from diffusing out of the regolith by the cold temperatures [3]. Previous measurements of the lunar atmosphere by the LACE experiment on Apollo 17, suggested the presence of cold trapped vola'tiles that were expelled by solar heating [4]. In situ composition and isotopic analyses of the lunar regolith will be required to establish the abundance, origin, and distribution of water-ice and other volatiles at the lunar poles. Volatile Analysis by Pyrolysis of Regolith (VAPoR) on the Moon using mass spectrometry is one technique that should be considered. The VAPoR pyrolysis-mass spectrometer (pyr-MS) instrument concept study was selected for funding in 2007 by the NASA Lunar Sortie Science Opportunities (LSSO) Program. VAPoR is a miniature version of the Sample Analysis at Mars (SAM) instrument suite currently being developed at NASA Goddard for the 2009 Mars Science Laboratory mission (Fig. 1).

Glavin, D. P.↗
DOE OSTI2022

Climate warming causes photobiont degradation and carbon starvation in a boreal climate sentinel lichen

The long-term potential for acclimation by lichens to changing climates is poorly known, despite their prominent roles in forested ecosystems. Although often considered “extremophiles,” lichens may not readily acclimate to novel climates well beyond historical norms. In a previous study, Evernia mesomorpha transplants in a whole-ecosystem climate change experiment showed drastic mass loss after 1 yr of warming and drying; however, the causes of this mass loss were not addressed. We examined the causes of this warming-induced mass loss by measuring physiological, functional, and reproductive attributes of lichen transplants. Severe loss of mass and physiological function occurred above +2°C of experimental warming. Loss of algal symbionts (“bleaching”) and turnover in algal community compositions increased with temperature and were the clearest impacts of experimental warming. Enhanced CO 2 had no significant physiological or symbiont composition effects. The functional loss of algal photobionts led to significant loss of mass and specific thallus mass (STM), which in turn reduced water-holding capacity (WHC). Although algal genotypes remained detectable in thalli exposed to higher stress, within-thallus photobiont communities shifted in composition toward greater diversity. The strong negative impacts of warming and/or lower humidity on Evernia mesomorpha were driven by a loss of photobiont activity. Analogous to the effects of climate change on corals, the balance of symbiont carbon metabolism in lichens is central to their resilience to changing conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Integrating density functional theory into reductive dechlorination research

Abstract Chlorinated organics have been frequently detected in groundwaters, threatening the quality of drinking water supplies worldwide. A promising method for groundwater remediation involves reductive dechlorination (RD), in which chlorine atoms are sequentially removed and substituted by hydrogen, producing less harmful byproducts. In this paper, for the first time, RD research is reviewed in light of the growing incorporation of density functional theory (DFT) as a research tool. DFT has been used to uncover a variety of reaction properties for a range of relevant groundwater pollutants, including 1,2,3‐trichloropropane, hexachlorobenzene, and various dioxins. DFT models have revealed the role of surface interactions in driving the kinetics of catalytically driven RD. Mechanisms involved with biologically mediated RD have also been elucidated with insights gleaned from DFT. Issues and challenges for future research are also discussed.

Das Schober, Jaya↗
DOE OSTI2021

Effect of chloride ingress on self-healing recovery of smart cementitious composite incorporating crystalline admixture and MgO expansive agent

Highlights: • Crack closure under wet/dry cycles in chloride solution is higher than the one in distilled water. • Element analysis shows that calcium is vital for crack healing either in water or chloride solution. • AFm is consumed by chloride ion to form Fs, and Fs were decomposed to AH{sub 3} by carbonation. • Soluble reactive silica reacts with calcium hydrate to form C-S-H gel to heal concrete cracks. • Expansion of magnesium hydroxide facilitates crack self-healing by interconnected network. In this study, the effect of chloride environment containing various concentrations of chloride ion (Cl{sup −}) on self-healing performance of pre-cracked cementitious composite containing crystalline admixture (CA) and MgO expansive agent (MEA) was investigated under wet-dry cycles in chloride solutions. The results revealed that the Cl{sup −} changed the mineralogy of self-healing products, and consequently, affected the crack closure ratio and mechanical strength recovery. When self-healing occurred in distilled water, a large amount of ettringite (AFt) were detected, whereas in Cl{sup −} solution, monosulfate (AFm) was consumed by Cl{sup −} to form Friedel's salt (Fs), and then the Fs was decomposed to Al(OH){sub 3}(AH{sub 3}) due to carbonation. During the multiphase conversion process, hydroxide (OH{sup −}) was released into crack solution, therefore the dissolved carbon dioxide (CO{sub 2}) concentration was increased. The carbonation of the crystals formed in cracks was accelerated with the volume expansion, which achieved rapid crack sealing but contributed little to the mechanical performance recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atmospheric Rivers in the Eastern and Midwestern United States Associated With Baroclinic Waves

Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic-scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long-wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations.

58 GEOSCIENCES↗
DOE OSTI2022

A portable fiber optic sensor for the luminescent sensing of cobalt ions using carbon dots

Cobalt is critical to energy-relevant technologies, and demand for cobalt will increase significantly with growing global adoption of renewables. However, supply chain stability is threatened by economic and geopolitical factors, incentivizing domestic cobalt production from alternative resources such as coal, coal utilization byproducts (e.g., ash, acid mine drainage) and electronic waste. Rapid, inexpensive, and portable characterization techniques are needed to reduce production costs associated with cobalt prospecting and process monitoring. Here, in this research, we develop a compact, portable fiber optic luminescent probe for cobalt using phosphorus and nitrogen co-doped carbon dots as the sensing material. The carbon dot emission overlaps well with the cobalt absorption band at ~510 nm, leading to a selective decrease in emission as a function of cobalt concentration. The system responds nearly instantly to the presence of cobalt, with detection limits of 0.7 and 3.5 ppm in water and pH 1.68 buffer, respectively, providing comparable performance to a commercial spectrometer at a significantly lower cost. Moreover, the sensor is selective for cobalt in the presence of 13 of the most common metal ions encountered in coal utilization byproducts and is responsive to cobalt when spiked into an acid mine drainage leachate sample, highlighting the sensor's potential for real-world deployment in challenging matrices. In addition, integrating the carbon dots with a filter paper substrate produced ‘test strip’ sensors that exhibited a selective and sensitive visual response to cobalt using a handheld UV lamp. Taken together, the sensing system represents a significant step forward in the development of low-cost practical sensors for high-value metals in complex streams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗
DOE OSTI2021

Laboratory Investigation of Gas Transport Through Variably Saturated Rock [Slides]

Project Overview: Noble gas fission products, such as xenon (Xe), are monitored to detect nuclear tests. For well-contained subsurface tests, transport to the surface will impact detected isotopic ratios, complicating event identification. Role of water saturation in subsurface transport is not well understood. Historic tests have taken place near or below the water table. To accurately predict breakthrough times and fractionation, gas transport must be characterized through intact rock with variable saturation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Nearshore coastal mapping

Two test sites of different water quality and bottom topography were used to test for maximum water depth penetration using the Skylab S-192 MSS for measurement of nearshore coastal bathymetry. Sites under investigation lie along the Lake Michigan coastline where littoral transport acts to erode sand bluffs and endangers developments along 1,200 miles of shore, and on the west coast of Puerto Rico where unreliable shoal location and depth information constitutes a safety hazard to navigation. The S-192 and S-190A and B provide data on underwater features because of water transparency in the blue/green portion of the spectrum. Depth of 20 meters were measured with the S-192 in the Puerto Rico test site. The S-190B photography with its improved spatial resolution clearly delineates the triple sand bar topography in the Lake Michigan test site. Several processing techniques were employed to test for maximum depth measurement with least error. The results are useful for helping to determine an optimum spectral bandwidth for future space sensors that will increase depth measurements for different water attenuation conditions where a bottom reflection is detectable.

Polcyn, F. C.↗
NASA NTRS1976

Radio detection of H2O in comet Bradfield (1974b)

Results of observations of comet Bradfield using the Haystack telescope are summarized with emphasis on the detection of the 1.35 cm emission line of water in the comet. The excitation of water and methyl cyanide in comets is briefly considered.

Jackson, W. M.↗
NASA NTRS1985

Use of satellite ocean color observations to refine understanding of global geochemical cycles

In October 1978, the first satellite-borne color sensor, the Coastal Zone Color Scanner (CZCS), was launched aboard Nimbus-7 with four visible and two infrared bands, permitting a sensitivity about 60 times that of the Landsat-1 multispectral scanner. The CZCS radiance data can be utilized to estimate ocean chlorophyll concentrations by detecting shifts in sea color, particularly in oceanic waters. The obtained data can be used in studies regarding problems of overfishing, and, in addition, in investigations concerning the consequences of man's accelerated extraction of nitrogen from the atmosphere and addition of carbon to the atmosphere. The satellite data base is considered along with a simulation analysis, and ships providing ground-truth chlorophyll measurements in the ocean.

Walsh, J. J.↗
NASA NTRS1989

Light scattering by randomly oriented crystals

The scattering phase function and the degree of linear polarization for small crystals oriented randomly in space have been computed using the geometric ray tracing theory and assuming that the crystals are homogeneous and isotropic. Calculations have been carried out for the main crystal geometries. Detection of halos from crystals other than hexagonal water ice is briefly discussed. The crystal size and shape parameters have also been averaged over some simple distributions in order to examine general light scattering properties of sharp-edged particles. A scalar physical optics correction has been developed for the geometric optics phase functions. Results can be applied to light scattering from regoliths and planetary rings, and possibly also to atmospheric halos. Retroreflecting crystals in the regolith would cause an opposition spike, a phenomenon observed for many bright satellites.

Muinonen, Karri↗
NASA NTRS1992

Evolution of near UV Halley's spectrum in the inner coma

A direct way to observe the photodissociation of water vapor in a cometary coma is to detect the OH prompt emission. This emission is shifted of delta lambda = 4 nm with respect to the OH 309 nm fluorescence band. The extended data set obtained with the three-channel spectrometer on-board Vega 2 reveals at short distance of the nucleus (i.e., less than 600 km) an excess of emission on the right wing of the OH band which may be interpreted as being mainly due to prompt emission.

Rousselot, Phillippe↗
NASA NTRS1995

The Submillimeter Wave Astronomy Satellite

The Submillimeter Wave Astronomy Satellite (SWAS) mission is dedicated to the study of star formation and interstellar chemistry. To carry out this mission, SWAS will survey dense (n(sub H2) greater than 10(exp 3) cm(exp -3)) molecular clouds within our galaxy in either the ground-state of a low-lying transition of five astrophysically important species: H2O, H2O-18, O2, CI, and CO-13. By observing these lines SWAS will: (1) test long-standing theories that predict that these species are the dominant coolants of molecular clouds during the early stages of their collapse to form stars and planets, and (2) supply heretofore missing information about the abundanceof key species central to the chemical models of dense interstellar gas. SWAS will employ two independent Schottky barrier diode mixers, passively cooled to approx. 150 K, coupled to a highly efficient 54 x 68 cm off-axis Cassegrain antenna. During its two year mission, SWAS will observe giant and dark cloud cores with the goal of detecting or setting an upper limit on the water abundance of 3 x 10(exp -6) and on th molecular oxygen abundances of 2 x 10(exp -6), both relative to H2. In addition, advantage will be taken of SWAS's relatively large beamsize of 3.2 x 4.0 arcminutes at 551 GHz and 3.6 x 4.5 arcminutes at 492 GHz to obtain large-area (approx. 1 deg x 1 deg) maps of giant and dark clouds in the CO-13 and CI lines. SWAS is scheduled for launch in mid-1995.

Melnick, Gary J.↗
NASA NTRS2001

The Mars Microbeam Raman Spectrometer (MMRS)

The Mars Microbeam Raman Spectrometer can identify minerals in situ, determine rock types and textures, provide some mineral chemistry, detect organic and biogenic materials, and identify bound water. Additional information is contained in the original extended abstract.

Haskin, L. A.↗
NASA NTRS2003

Micro-optical Distributed Sensors for Aero Propulsion Applications

The objective of this research is to develop micro-opto-mechanical system (MOMS)-based sensors for time- and space-resolved measurements of flow properties in aerodynamics applications. The measurement technique we propose uses optical resonances in dielectric micro-spheres that can be excited by radiation tunneling from optical fibers. It exploits the tunneling-induced and morphology-dependent shifts in the resonant frequencies. The shift in the resonant frequency is dependent on the size, shape, and index of refraction of the micro-sphere. A physical change in the environment surrounding a micro-bead can change one or more of these properties of the sphere thereby causing a shift in frequency of resonance. The change of the resonance frequency can be detected with high resolution by scanning a frequency-tunable laser that is coupled into the fiber and observing the transmission spectrum at the output of the fiber. It is expected that, in the future, the measurement concept will lead to a system of distributed micro-sensors providing spatial data resolved in time and space. The present project focuses on the development and demonstration of temperature sensors using the morphology-dependent optical resonances although in the latter part of the work, we will also develop a pressure sensor. During the period covered in this report, the optical and electronic equipment necessary for the experimental work was assembled and the experimental setup was designed for the single sensor temperature measurements. Software was developed for real-time tracking of the optical resonance shifts. Some preliminary experiments were also carried out to detect temperature using a single bead in a water bath.

Arnold, S.↗
NASA NTRS2003

Jupiter Atmospheric Science with JIMO: Linking Science Objectives and Measurement Goals

Although the primary focus of the Jupiter Icy Moons Orbiter (JIMO) mission will be the characterization and study of Jupiter's icy moons, there will be opportunities throughout the mission for unprecendented observations of Jupiter. With an adaptable suite of payload instruments, the atmospheric data collected by JIMO can help to answer fundamental questions about the largest planet in our solar system that remain after (or were generated by) previous spacecraft reconnaissance (e.g. Voyager, Galileo, and Cassini). Near-IR (0.7-4 micron) spectral imaging will most likely be used to identify mineralogies and ices on the Jovian satellites by virtue of their spectral signatures. This same capability is very well tailored for studies of Jovian atmospheric dynamics and structure. Near-IR methane absorption bands allow 2-D mapping of the horizontal wind field at size scales to tens of kms, as well as the height dependence of this field above the ammonia cloud deck (700 to a few mbar), constraining current models of atmospheric vertical structure. Likewise, atmospheric ice aerosols with unique spectroscopic signatures (ammonia ice near 1.5, 2.0, and 2.8 microns and water ice between 3.0 - 3.5 microns) can be detected and mapped using spectral difference imaging or spectrally inclusive principal-component methods. Spectral imaging of the Jovian aurora via (3)H(+) emission lines between 3 - 4 microns can be used to spatially map the interplay between the satellites) Jupiter's magnetosphere, and Jupiter's atmosphere. Each of these measurements addresses one or more fundamental questions related to the energy balance in Jupiter's atmosphere. All of these tunable imaging objectives can be achieved using acousto-optic tunable filters (AOTF's), which have been used for years in ground-based observing instruments and which have been proposed for numerous planetary missions. The application of this technology to the science objectives of both the icy satellites and Jovian atmospheric components of the JIMO mission will be discussed.

Chanover, N. J.↗